A Survey on Vision-Language-Action Models for Embodied AI

[2405.14093] A Survey on Vision-Language-Action Models for Embodied AI Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Robotics arXiv:2405.14093 (cs) [Submitted on 23 May 2024 ( v1 ), last revised 1 May 2026 (this version, v8)] Title: A Survey on Vision-Language-Action Models for Embodied AI Authors: Yueen Ma , Zixing Song , Yuzheng Zhuang , Jianye Hao , Irwin King View a PDF of the paper titled A Survey on Vision-Language-Action Models for Embodied AI, by Yueen Ma and 4 other authors View PDF HTML (experimental) Abstract: Embodied AI is widely recognized as a cornerstone of artificial general intelligence (AGI) because it involves controlling embodied agents to perform tasks in the physical world. Building on the success of large language models (LLMs) and vision-language models (VLMs), a new category of multimodal models -- referred to as vision-language-action (VLA) models -- has emerged to address language-conditioned robotic tasks in embodied AI by leveraging their distinct ability to generate actions. The recent proliferation of VLAs necessitates a comprehensive survey to capture the rapidly evolving landscape. To this end, we present the first survey on VLAs for embodied AI. This work provides a detailed taxonomy of VLAs, organized into three major lines of research. The first line focuses on individual components of VLAs. The second line is dedicated to developing VLA-based control policies adept at predicting low-level actions. The third line comprises high-level task planners capable of decomposing long-horizon tasks into a sequence of subtasks, thereby guiding VLAs to follow more general user instructions. Furthermore, we provide an extensive summary of relevant resources, including datasets, simulators, and benchmarks. Finally, we discuss the challenges facing VLAs and outline promising future directions in embodied AI. A curated repository associated with this survey is available at: this https URL . Comments: Project page: this https URL Subjects: Robotics (cs.RO) ; Computation and Language (cs.CL); Computer Vision and Pattern Recognition (cs.CV) MSC classes: 68T40 (Primary) 68T45, 68T50, 68T07 (Secondary) ACM classes: I.2.9; I.2.10; I.2.7; I.2.6 Cite as: arXiv:2405.14093 [cs.RO] (or arXiv:2405.14093v8 [cs.RO] for this version) https://doi.org/10.48550/arXiv.2405.14093 Focus to learn more arXiv-issued DOI via DataCite Journal reference: IEEE Transactions on Neural Networks and Learning Systems (Early Access), 2026 Related DOI : https://doi.org/10.1109/TNNLS.2025.3650584 Focus to learn more DOI(s) linking to related resources Submission history From: Yueen Ma [ view email ] [v1] Thu, 23 May 2024 01:43:54 UTC (2,337 KB) [v2] Thu, 28 Nov 2024 09:18:10 UTC (1,170 KB) [v3] Mon, 3 Mar 2025 03:19:31 UTC (1,491 KB) [v4] Tue, 4 Mar 2025 08:24:20 UTC (1,491 KB) [v5] Sun, 31 Aug 2025 06:51:08 UTC (2,256 KB) [v6] Mon, 19 Jan 2026 07:34:10 UTC (2,625 KB) [v7] Wed, 4 Feb 2026 06:41:11 UTC (2,684 KB) [v8] Fri, 1 May 2026 01:50:44 UTC (2,757 KB) Full-text links: Access Paper: View a PDF of the paper titled A Survey on Vision-Language-Action Models for Embodied AI, by Yueen Ma and 4 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.RO < prev | next > new | recent | 2024-05 Change to browse by: cs cs.CL cs.CV References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... 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